class_docstr: Iterator
code: def train_examples(
      self,
  ):
      # Filters
      trainer_id = int(os.getenv("PADDLE_TRAINER_ID", "0"))
      trainer_num = int(os.getenv("PADDLE_TRAINERS_NUM", "1"))
      count_line = 0
  
      np.random.shuffle(self.train_idx)
      for idx in self.train_idx:
          count_line += 1
          if count_line % trainer_num == trainer_id:
              yield idx
  
imports: import os
  import tqdm
  import yaml
  import pgl
  import time
  import copy
  import numpy
  import os.path
  from pgl.utils.logger import log
  from pgl.graph import Graph
  from pgl import graph_kernel
  from pgl.sampling.custom import subgraph
  from ogb.lsc import MAG240MDataset, MAG240MEvaluator
  from dataset.base_dataset import BaseDataGenerator
  import time
label_desc: Use image node_id 3 for calling the MAG240M obj's underlying member method code with example usage: obj.train_examples() without return types